Downregulation of Cinnamoyl-Coenzyme A Reductase in Poplar: Multiple-Level Phenotyping Reveals Effects on Cell Wall Polymer Metabolism and Structure
Bibliographic record
Abstract
Cinnamoyl-CoA reductase (CCR) catalyzes the penultimate step in monolignol biosynthesis. We show that downregulation of CCR in transgenic poplar (Populus tremula x Populus alba) was associated with up to 50% reduced lignin content and an orange-brown, often patchy, coloration of the outer xylem. Thioacidolysis, nuclear magnetic resonance (NMR), immunocytochemistry of lignin epitopes, and oligolignol profiling indicated that lignin was relatively more reduced in syringyl than in guaiacyl units. The cohesion of the walls was affected, particularly at sites that are generally richer in syringyl units in wild-type poplar. Ferulic acid was incorporated into the lignin via ether bonds, as evidenced independently by thioacidolysis and by NMR. A synthetic lignin incorporating ferulic acid had a red-brown coloration, suggesting that the xylem coloration was due to the presence of ferulic acid during lignification. Elevated ferulic acid levels were also observed in the form of esters. Transcript and metabolite profiling were used as comprehensive phenotyping tools to investigate how CCR downregulation impacted metabolism and the biosynthesis of other cell wall polymers. Both methods suggested reduced biosynthesis and increased breakdown or remodeling of noncellulosic cell wall polymers, which was further supported by Fourier transform infrared spectroscopy and wet chemistry analysis. The reduced levels of lignin and hemicellulose were associated with an increased proportion of cellulose. Furthermore, the transcript and metabolite profiling data pointed toward a stress response induced by the altered cell wall structure. Finally, chemical pulping of wood derived from 5-year-old, field-grown transgenic lines revealed improved pulping characteristics, but growth was affected in all transgenic lines tested.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".